Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Spatial whitening in the retina may be necessary for V1 to learn a sparse representation of natural scenes

View ORCID ProfileEric McVoy Dodds, View ORCID ProfileJesse Alexander Livezey, Michael Robert DeWeese
doi: https://doi.org/10.1101/776799
Eric McVoy Dodds
1Department of Physics, University of California, Berkeley, CA 94720, USA
2Redwood Center for Theoretical Neuroscience and Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Eric McVoy Dodds
Jesse Alexander Livezey
1Department of Physics, University of California, Berkeley, CA 94720, USA
2Redwood Center for Theoretical Neuroscience and Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
3Lawrence Berkeley National Laboratory, Berkeley, CA 94720
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jesse Alexander Livezey
Michael Robert DeWeese
1Department of Physics, University of California, Berkeley, CA 94720, USA
2Redwood Center for Theoretical Neuroscience and Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: deweese@berkeley.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Retinal ganglion cell outputs are less correlated across space than are natural scenes, and it has been suggested that this decorrelation is performed in the retina in order to improve efficiency and to benefit processing later in the visual system. However, sparse coding, a successful computational model of primary visual cortex, is achievable under some conditions with highly correlated inputs: most sparse coding algorithms learn the well-known sparse features of natural images and can output sparse, high-fidelity codes with or without a preceding decorrelation stage of processing. We propose that sparse coding with biologically plausible local learning rules does require decorrelated inputs, providing a possible explanation for why whitening may be necessary early in the visual system.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted September 20, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Spatial whitening in the retina may be necessary for V1 to learn a sparse representation of natural scenes
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Spatial whitening in the retina may be necessary for V1 to learn a sparse representation of natural scenes
Eric McVoy Dodds, Jesse Alexander Livezey, Michael Robert DeWeese
bioRxiv 776799; doi: https://doi.org/10.1101/776799
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Spatial whitening in the retina may be necessary for V1 to learn a sparse representation of natural scenes
Eric McVoy Dodds, Jesse Alexander Livezey, Michael Robert DeWeese
bioRxiv 776799; doi: https://doi.org/10.1101/776799

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4658)
  • Biochemistry (10313)
  • Bioengineering (7636)
  • Bioinformatics (26241)
  • Biophysics (13481)
  • Cancer Biology (10648)
  • Cell Biology (15361)
  • Clinical Trials (138)
  • Developmental Biology (8463)
  • Ecology (12776)
  • Epidemiology (2067)
  • Evolutionary Biology (16794)
  • Genetics (11372)
  • Genomics (15431)
  • Immunology (10580)
  • Microbiology (25087)
  • Molecular Biology (10172)
  • Neuroscience (54233)
  • Paleontology (398)
  • Pathology (1660)
  • Pharmacology and Toxicology (2883)
  • Physiology (4326)
  • Plant Biology (9213)
  • Scientific Communication and Education (1582)
  • Synthetic Biology (2545)
  • Systems Biology (6761)
  • Zoology (1458)